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Continuous Improvement is Not a Valuable Concept Because It Lacks Measurement Techniques

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1. Introduction

Employee involvement and commitment is strongly related to the success of continuous improvement (Coyle-Shapiro 2002; Jurburg et al. 2017; Lleo et al. 2017; Costa et al. 2019). Consequently, various antecedents are reported in the production and operations management literature to increase employee involvement and commitment in improvement programmes, such as empowerment, participation in goal setting, decentralised decision-making, performance measurement system, financial and non-financial rewards, training and having a common improvement method, i.e. a standard set of steps and tools used during improvement projects that promotes a common understanding of how to come to improvements (Dow, Samson, and Ford 1999; Cua, McKone, and Schroeder 2001; Brun 2011; Sila and Ebrahimpour 2003; Marodin and Saurin 2013; Costa et al. 2019). Training has indeed been promoted as an important mechanism to facilitate continuous improvement as it increases employee's self-efficacy for continuous improvement (Ahmed, Loh, and Zairi 1999; Bevilacqua, Ciarapica, and De Sanctis 2017; Aloini, Martini, and Pellegrini 2011). Anand et al. (2009) also described that organisations use systematic training initiatives at different organisational levels to train in a company-wide, structured improvement method with corresponding tools and so develop a climate and infrastructure for continuous improvement. However, the supposed enhancing effect of training in such a common improvement method on either employee involvement and on the effectiveness of continuous improvement has, to our best knowledge, not yet been scientifically validated. Though some case studies show that improvement programmes in practice start with training in a common improvement method and corresponding tools (Netland 2016; Anand, Chhajed, and Delfin 2012), there is little empirical evidence that training in such a common improvement method is indeed effective. What's more, Costa et al. (2019) found that training only indirectly impacts employee engagement in continuous improvement. In addition, Nair, Malhotra, and Ahire (2011) state that it is also important to maintain a balance between training and the adherence to a structured improvement method and corresponding tools and the creation of a supportive and creative environment. In complex and uncertain organisation environments, such a mandatory common method for problem solving and improvement may not necessarily facilitate employees to improve their work as it requires more creativity for which a structured, organisation-wide improvement method may be too rigid (Nair, Malhotra, and Ahire 2011). In addition, such a common improvement method may be too complex and time consuming for very simple improvement projects (Linderman et al. 2003). Nevertheless, a lot of money is invested in general training programmes for continuous improvement and/or in company-wide improvement methods as most 'deployment models' used in practice start with the mass-training of employees (Lameijer, De Mast, and Does 2017; Hoerl and Snee 2013). Note that the global market in 2018 for operations management services was estimated to be worth around $70 billion, of which 2 percent is spent on off-the-shelf improvement methods and associated training (https://www.consultancy.eu/consulting-industry/operations-consulting). Since some of these training and improvement programmes are not as successful in practice as initially expected (Negrão, Godinho Filho, and Marodin 2017), the question remains whether it is worth the investment? Do training in and the use of a standard improvement method lead to higher levels of employee involvement and hence higher levels of continuous improvement? The objective and contribution of this article is therefore to study the mediating effect of employee involvement in the relationship between training and continuous improvement, and the possible moderating effect of a common improvement method on the relationship between training in continuous improvement and employee involvement.

The structure of this paper is as follows: section 2 presents the research model and related hypotheses based on a brief review of the relevant literature. Data, variables and research method to validate our research model are discussed in section 3 and the statistical results are described in section 4. Discussion of the findings and the implications for practice and (future) research are given in section 5.

2. Literature review and hypotheses development

2.1. Continuous improvement

Continuous improvement is the systematic effort to seek out and apply new ways of doing work i.e. actively and repeatedly making process improvements (Anand et al. 2009). It is a learning process of gradual accumulation of experimentations whereby a continuous stream of incremental innovations emerge (Bessant and Francis 1999). Continuous improvement constitutes the development of specific abilities within the organisation, for example the ability to find and solve problems systematically or the ability to share knowledge across intra-organisational boundaries (Bessant, Caffyn, and Gallagher 2001). It requires an organisation-wide commitment and arrangements to support the analysis and improvement of procedures, processes and products & services. Such a capability includes an organisational infrastructure and climate that constantly guides organisational members to strive for continuous improvement and learning (Anand et al. 2009).

Continuous improvement leads to higher operational and financial performance because of the elimination of unnecessary variability (Hopp and Spearman 2004), the reduction of non-value added activities and hence an increase of customer value and satisfaction (Singh and Singh 2015). In addition, continuous improvement seems to function as a kind of a fitness factor that enlarges the impact of other practices on performance (Bortolotti et al. 2015), and is hence a source of competitive advantage (Sanchez and Blanco 2014; de Menezes, Wood, and Gelade 2010).

Enabling factors of continuous improvement are leadership commitment (Zu, Robbins, and Fredendall 2010), the creation of a continuous improvement culture (Irani, Beskese, and Love 2004), empowerment (Hirzel, Leyer, and Moormann 2017), participative goal setting for continuous improvement (Jurburg et al. 2017), information provisioning and visual performance management (Eaidgah et al. 2016), employee involvement (Lleo et al. 2017), a structured method (Yang, Lee, and Cheng 2016) and training (Jurburg et al. 2017).

2.2. Training and employee involvement in continuous improvement

Training is needed for developing employee involvement and participation in various quality and process improvement concepts (Kim, Kumar, and Kumar 2012). Researchers have confirmed that training is a basic factor in the success of quality management implementation (Flynn, Sakakibara, and Schroeder 1995; Anderson, Rungtusanatham, and Schroeder 1994; Kitapçi and Sezen 2007). Based on a multisite, longitudinal case study Netland (2016) stated that 'training and education', 'commitment and involvement' and 'participation and empowerment' are the most important critical success factors of lean management, but did not indicate how these factors are related, let alone how they reinforce each other. Nevertheless, training is considered an enabling HR-practice to empower employees to enhance their self-efficacy and commitment for continuous improvement (Jurburg et al. 2017). A well-trained and committed employee tends to work more efficiently and effectively to improve performance (Kim, Kumar, and Kumar 2012). In contrast, lack of training and lack of commitment are cited as major causes of unsuccessful continuous improvement initiatives (Cua, McKone, and Schroeder 2001; McLean, Antony, and Dahlgaard 2017).

Though employee involvement is key to the success of continuous improvement (Bakotić and Rogošić 2017; Longenecker, Scazzero, and Stansfield 1994), the contribution of employees to continuous improvement not only depends on one's willingness and interest in participating, but is also determined by one's personal abilities with regard to continuous improvement (Lok et al. 2005; Lam, O'Donnell, and Robertson 2015). It is therefore essential that employees feel equipped with all relevant information, skills and competencies to engage in continuous improvement activities. Indeed, equipped employees feel empowered and are more involved in improvement activities, which is crucial for continuous improvement programmes (Lillrank, Shani, and Lindberg 2001; Swartling and Olausson 2011). Training provides employees the skills and knowledge necessary to participate in continuous improvement activities (Jurburg et al. 2017) which encourages employees to be more involved in continuous improvement (Longenecker, Scazzero, and Stansfield 1994). Creating an infrastructure in which employees on various levels are trained and empowered in the continuous improvement process, will lead to a more successful continuous cycle of improvement that can serve as a dynamic capability (Anand et al. 2009). This concurs with the finding of Hirzel, Leyer, and Moormann (2017) that there is a positive link between the training of employees in the principles and tools of continuous improvement and their behaviour as a foundation for the implementation of continuous improvement, which can be explained by the theory of structural empowerment: the acquisition of required knowledge to undertake continuous improvement activities, as well as understanding of the goal of continuous improvement to realise the impact of continuous improvement in one's daily work is positively related to one's contribution to continuous improvement (Lillrank, Shani, and Lindberg 2001). Hence, we have the following hypothesis:

H1: The extent of training for continuous improvement is positively related to employee involvement in continuous improvement

H2: Employee involvement is positively related to continuous improvement

This implies the following hypothesis:

H3: Employee involvement mediates the relationship between training and continuous improvement

2.3. Training, common improvement method and employee involvement

The general view of empirical researchers is that training is needed to develop employee participation in organisational quality management and improvement efforts (Flynn, Sakakibara, and Schroeder 1995; Ravichandran and Rai 2000; Kaynak 2003; Jurburg et al. 2017). 'Unless employees know how to implement the concepts or techniques of quality management and process improvement in their jobs, employees may resist and lack commitment to change, instead of giving a positive impetus or benefit (Kim, Kumar, and Kumar 2012)'. Negrão, Godinho Filho, and Marodin (2017), for instance, found that to increase employee autonomy and involvement it is required that organisations invest time and effort in training and developing employees. Training enables employees to learn the technical aspects of process improvement (i.e. decision making tools and methods) but it also provides the groundwork for establishing a foundation for social interaction around continuous improvement in order to develop a common understanding about continuous improvement and to increase employees' perceived self-efficacy for continuous improvement (Linderman, Schroeder, and Sanders 2010). However, training in the principles of continuous improvement is not the only mechanism to build a common understanding of continuous improvement; establishing a common problem solving language can also help organisational members with dissimilar backgrounds to come together and develop a common understanding about continuous improvement. Proponents of continuous improvement and related business improvement methods have therefore argued that training and the use of a common improvement method will increase the skill variety of jobs to a level that employees become more engaged and involved in continuous improvement; see for instance Adler, Goldoftas, and Levine (1999); de Treville and Antonakis (2006); Axtell et al. (2000). Such a structured problem solving method consisting of a prescribed sequence of steps to follow, complemented with a set of improvement tools, is key in any quality improvement programme (Choo, Linderman, and Schroeder 2007) to increase employee's self-efficacy and involvement (Adler, Goldoftas, and Levine 1999). Hence, we hypothesise a positive relation between the use of a common improvement method and employee involvement. However, de Treville and Antonakis (2006) proposed that a structured improvement method, such as lean management, will result in increased skill variety in situations where workers receive training and participate in problem solving provided that such an improvement method is not too rigid, as that may demotivate people to participate in continuous improvement. When employees have the impression that the company-wide improvement method is being forced and training is predominantly used to strengthen it, or when employees consider the common improvement method as too rigid, then the adherence to the use of a common improvement method and training for continuous improvement becomes counterproductive (Parker 2014). Also, when employees have the impression that the common improvement method is too extensive or too technical, which is sometimes the case with lean six sigma (Lameijer et al. 2016), they may also see it as a burden and extra training in combination with the mandatory use of a common improvement method may have the opposite effect. Linderman et al. (2003) also argued that relatively simple improvement projects could in fact be adversely affected by extensive training. Consequently, we hypothesise a negative interaction between training for continuous improvement and the mandatory use of a common improvement method, such that the higher the level of (adherence to) a common improvement method, the weaker the positive effect of training for continuous improvement on employee involvement in continuous improvement.

H4: A common improvement method is positively related to employee involvement in continuous improvement.

H5: There is a negative interaction between training for continuous improvement and the adherence to a common improvement method, such that the higher the adherence to a common improvement method, the weaker the positive effect of training for continuous improvement on employee involvement.

2.4. Employee involvement, participative goal setting and continuous improvement

Empowerment is also an important antecedent of continuous improvement. Spreitzer (1995), for instance, argued that empowerment leads to a proactive orientation towards the job and related work processes. Indeed, empowered employees actively create, shape and alter their working environments (Parker and Collins 2010); they are likely to have an open attitude towards errors, seeing them not as failures but as opportunities for learning and further improvements and innovation. Empowered employees are more proactive and continuously seek opportunities to improve and revise work processes, and seek innovative solutions to more complex work problems (Kirkman and Rosen 1999). Empowerment is associated with frequently taking action on problems and improve the quality of work by initiating changes in the way work is carried out (Wellins, Byham, and Wilson 1991) which leads to higher job performance and productivity (Spreitzer 1995; Conger and Kanungo 1988; Kirkman and Rosen 1999). Hence, empowerment is related to exploitative learning. In addition, empowered employees feel safe and trust their leaders to support and reward them for creative initiatives, even when these initiatives fail to meet their expected goals (Caniëls, Neghina, and Schaetsaert 2017) Empowered employees, who are also responsible for quality and continuous improvement, frequently collect data to measure possible discrepancies at work, which allow them to continuously improve their work and related processes (Kirkman and Rosen 1999). Continuous improvement therefore benefits from a high degree of employee commitment and empowerment - that is why employee involvement and participatory goal setting for continuous improvement is so important. Indeed, management support for continuous improvement includes the stimulation of active participation and involvement in improvement activities (Zu, Robbins, and Fredendall 2010) as participation in goal setting leads to greater intrinsic motivation and a greater sense of empowerment (Linderman, Schroeder, and Choo 2006). Indeed, Stansfield and Longenecker (2006) found that participation in goal setting and timely feedback will lead to improved work performance, greater efficiency, and the establishment of more challenging goals. The expectation is therefore that there will be more continuous improvement if trained employees (which increases self-efficiency) have clear CI-related goals and are allowed to determine these themselves. Hence, we hypothesise a positive interaction between participation in goal setting for continuous improvement and employee involvement in continuous improvement, such that the higher the level of participation in goal setting, the stronger the positive effect of employee involvement on the extent of continuous improvement in the organisation.

H6: Participation in goal setting for continuous improvement positively moderates the relationship between employee involvement and continuous improvement.

In sum, our research model is illustrated in Figure 1.

Figure 1. Research model.

3. Methodology

3.1. Data collection

The sample was Dutch managers, with various management positions ranging from team leader to senior manager, working in various types of industries. All of the managers were enrolled in a part-time executive master's course at a Dutch business school. Because the research question and the associated constructs of our survey were not primarily the subject of the enrolled course, we assumed that this would not cause a problematic sample bias. The absence of any overly skewed variables confirmed this assumption. An email with a link to a web-survey was sent to 225 participants prior to the beginning of the course. Participants were informed that non-consent did not in any way affect their role as a business school participant. About 95% of the participants completed the questionnaire. Most participants (99%) gave informed consent to use the data for research (N 0 = 211). Removing 3 cases with missing values on some of the variables of this study resulted in a final sample size of 208 cases. Respondents worked full-time and the average tenure in the organisation was 9.76 years (SD = 6.07). The average age of the respondents was 41.55 years (range = 23 to 58; SD = 8.02), and 75% were men.

3.2. Measures, scale development and purification

We measured the variable training with three items based on the scales of Saraph, Benson, and Schroeder (1989) and Cua, McKone, and Schroeder (2001), where we reworded the items to fit the context of continuous improvement (CI). The value of Cronbach's alpha was .83. To measure continuous improvement we used four items of the scale of Huang, Rode, and Schroeder (2011) with a value of Cronbach's alpha of .73. Employee involvement was measured with items based on McLachlin (1997) and Cua, McKone, and Schroeder (2001) with a value of Cronbach's alpha of .79. In addition, we developed a new measure for common improvement method based on the work of Zu, Fredendall, and Douglas (2008) that had a value of Cronbach's alpha of .85. Finally, we developed a measure for participative goal setting for CI based on items from the participative decision-making scale of the empowering leadership questionnaire of Arnold et al. (2000) where we reworded the items to fit the context of continuous improvement, with a value of Cronbach's alpha of .79; see in the Appendix. Descriptive statistics and a correlation matrix for all constructs (with the values of Cronbach alpha on the diagonal) are presented in .

Table 1. Correlation matrix.

Construct validity was examined through the adequacy of the model's fit of a confirmatory factor analysis for which AMOS 23 was used. Results indicate adequate fit for the measurement model with a χ 2 of 207.787 and 125 degrees of freedom, CFI = .948, IFI = .949, TLI/NNFI = .937 and RMSEA = .057 (Browne and Cudeck 1992). For satisfactory convergent validity, the estimated parameters between the latent variables and their indicators should be at least .50 (Hair et al. 1998). Results in in the Appendix indicate that convergent validity is supported since all constructs passed this test.

To test for discriminant validity, we performed chi-square difference tests on the result of CFAs for the unconstrained model versus the constrained model for each pair of variables, where the covariance parameter of the pair of variables was constrained at 1 in the constrained model and set to be free in the unconstrained model. For satisfactory discriminant validity, the χ 2 -difference values should be greater than 3.84 (Kim, Kumar, and Kumar 2012; Ng et al. 2015). The χ 2 -difference values ranged from 19.6 to 86.7 indicating satisfactory discriminant validity; see in the Appendix. Cronbach's alpha exceeds .60 for all constructs, which indicates satisfactory reliability. In addition, all Cronbach alpha values were greater than the correlations, which also indicates satisfactory discriminant validity; see e.g. Kaynak (2003).

3.3. Control variables and common method variance

We used size, tenure and type of industry as control variables. Size was measured in the number of full time equivalents (logarithmised). Tenure was measured by years of experience in the current job or a job with a comparable function. Note that the control variables size and tenure of the respondent were not associated to the main variables of this study; see . Tenure is negatively related to organisational size, which implies that tenure of the respondents decrease with the size of the organisation.

To prevent common method bias we first separated the dependent and independent variable items over the length of the survey instrument. We also used Harman's one-factor test to assess whether common method bias exists (Podsakoff et al. 2003), for which we entered all items of the variables under study into an unrotated exploratory factor analysis to test whether the majority of the variance could be explained by a single factor, but this was not the case. Finally, we tested the measurement model with a common latent factor in a confirmatory factor analysis which results in a common variance of 16%. We therefore conclude that the tests for reliability, validity, overall model fit and common method bias provide adequate support of the appropriateness of the model constructs.

4. Results

The procedure applied to test our research model is as follows. First, we tested a mediation model with continuous improvement as the dependent variable, training as the independent variable and employee involvement as the hypothesised mediator. Subsequently, we tested the moderation effect of common improvement method in the relationship between training and employee involvement by regressing employee involvement on the control variables and subsequently on training, common improvement method (CIM), and the interaction term training × common improvement method (CIM). With a similar procedure we tested the moderation effect of participative goal setting for continuous improvement in the relationship between employee involvement and continuous improvement. Finally, we evaluated the conditional indirect effect(s) of different values of the moderator(s) in the moderated-mediation model.

4.1. Mediation

To test whether employee involvement is a mediator in the relationship between training and continuous improvement, we employed multiple regression analysis for which we used SPSS 24 with the Process plugin (Hayes 2013). Basically the analysis comes down to three separate regression models; see . The first model tests whether training predicts employee involvement, for which we regressed employee involvement on training and the control variables. The model was significant with R 2 = .27, F(12,195) = 5.89, p < .001 and resulted in a significant coefficient for training (β = .45, t(195) = 7.05, p < .001) and for the dummy variable representing the finance and insurance industry (β = .15, t(195) = 2.00, p < .05) indicating that employee involvement in continuous improvement is structurally more common in this type of industry. Hypothesis 1 was confirmed based on this model. Model 2, the total effect model that tests the total effect of training on continuous improvement, was significant with R 2 = .23, F(12,195) = 4.92, p < .001 and resulted in a significant coefficient for training (β = .43, t(195) = 6.62, p < .001) and for the dummy variable representing the public service sector (β = −.14, t(195) = −2.63, p < .05) indicating that continuous improvement is structurally more uncommon in this type of service sector. Finally, we regressed continuous improvement on the variables training, employee involvement and the control variables to test the indirect effect of training via employee involvement. Model 3 was significant with R 2 = .42, F(13,194) = 10.75, p < .001 and resulted in significant coefficients for training (β = .20, t(194) = 3.22, p < .01), for employee involvement (β = .50, t(194) = 7.88, p < .001) and for the dummy variables representing the public service sector (β = −.14, t(194) = −2.03, p < .05) and the professional, scientific and technical services sector (β = −.12, t(194) = −1.99, p < .05). We therefore conclude that hypothesis 2 was confirmed. Note however, that the dummy variable associated with public service sector is negatively associated with continuous improvement in both the direct effect model and the indirect effect model, which means that continuous improvement is structurally more uncommon in this type of industry.

Table 2. Results of mediation analysis.

Mediation analysis shows that employee involvement acts as a partial mediator as the effect of training on continuous improvement drops from .43 to .20 when the mediator was included in the model. The effect size of the mediating influence of employee involvement is however substantial and significant given a Z-score of 4.88 (κ 2 = .13, p < . 001). Hence, hypothesis 3 was confirmed, i.e. there is not only an indirect relationship between training and continuous improvement via employee involvement, but also a direct relationship.

4.2. Moderation

To test the moderation effect of a common improvement method in the relationship between training and employee involvement, we employed a hierarchical regression analysis in which we first regressed employee involvement on the control variables and subsequently on training, common improvement method (CIM), and the interaction term training × common improvement method (CIM) with centred variables; see for the results. Model 4a represents the regression of employee involvement on the control variables. Consistent with the results of model 1 in , this model also resulted in a significant coefficient for the dummy variable representing the finance and insurance industry (β = .22, t(196) = 2.70, p < .01). Model 4 b, representing step 2 of the hierarchical regression analysis, was significant with F(14,193) = 21.63, R 2 = .31, p < .001. The coefficients for training (β = .33, t(193) = 4.26, p < .001) and for common improvement method (β = .25, t(193) = 3.09, p < .01) were positive and significant, while the coefficient for the interaction term was negative and significant (β = –.13, t(193) = –2.13, p < .05). Hence, hypotheses 4 and 5 were confirmed.

Table 3. Results of hierarchical regression analysis for employee involvement.

To evaluate the effect of a common improvement method as a moderator in the relationship between training and employee involvement, we plotted the effect (see Figure 2) by testing the simple slopes for respondents with higher levels (i.e. one standard deviation above the mean), average levels, and lower levels of common improvement method to determine the nature of the training × common improvement method interaction. Training was significantly related to employee involvement for lower levels of common improvement method (b = .40, p < .001) for average levels of common improvement method (b = .29, p < .001) and for higher levels of common improvement method (b = .18, p < .05), though the effect of training on employee involvement diminishes with increasing levels of common improvement method.

Figure 2. Interaction oftraining and common improvement method on employee involvement.

A similar procedure was used to test the moderation effect of participative goal setting in the relationship between employee involvement and continuous improvement; see for the results. Step 2 of the hierarchical regression analysis (which was significant given F(15,192) = 38.45, R 2 = .44, p < .001) resulted in positive and significant coefficients for training (β = .16, t(192) = 2.70, p < .01), employee involvement (β = .32, t(192) = 4.32, p < .001) and participative goal setting for CI (β =.30, t(192) = 4.38, p < .001), but the interaction term was non-significant. Hence, we have to reject hypothesis 6; see . In addition, the coefficients for the dummy variables for the sectors wholesale trade, professional, scientific and technical services, and public services were all negative and significant at the .05 level, indicating that continuous improvement structurally occurs less in these sectors.

Table 4. Results of regression analysis for continuous improvement.

The direct effect of training on continuous improvement when also the variables employee involvement and participative goal setting for CI were included was .16 (t = 2.70, p < .01). To evaluate the conditional indirect effect of training on continuous improvement due to common improvement method as the significant moderator, we determined the effects of training on continuous improvement at low (i.e. minus one standard deviation from the mean), average (the mean) and high levels of common improvement method, which were .12, .09 and .06 respectively. This indicates that the higher the adherence to a common improvement method, the lower the indirect effect of training via employee involvement on continuous improvement.

5. Discussion

5.1. Theoretical implications

The results of this study show that training positively impacts continuous improvement, though this relationship is partially mediated by the extent of employee involvement. This corresponds with the common view of empirical researchers such as Flynn, Sakakibara, and Schroeder (1995), Ravichandran and Rai (2000), and Kaynak (2003) that training is needed for developing employee participation in improvement efforts. It also shows that having a company-wide common improvement method that guides employees how to continuously improvement their work-processes is positively related to employee involvement in continuous improvement. Both infrastructural mechanisms help organisational members with dissimilar backgrounds to come together and develop a common understanding about how to conduct continuous improvement activities. However, our study provides a more nuanced picture than the current literature on this topic provides: training for continuous improvement and the use of a common improvement method indeed facilitate employee involvement in continuous improvement, but if the training and the adherence to the use of a standard improvement method becomes too rigid, then these mechanisms may hamper employee creativity and discourage employees and the increase in employee involvement due to training for continuous improvement is dampened. Continuous improvement may indeed flourish if it is supported by an infrastructure of which training and having a common improvement method are important parts (Anand et al. 2009), but it is required that employees perceive this as helpful in their work.

An additional finding of this study is that participative goal setting positively relates to continuous improvement, though we did not find an interaction between employee involvement and participative goal setting for continuous improvement like we hypothesised. Though employee participation in goal setting is found to be important for continuous improvement (Oliver 2009) our study shows that it does not strengthen employee involvement. This concurs to the results of Erez and Arad (1986) that participation in setting goals leads to higher commitment than curtly telling people what to do with no explanation, but it does not lead to (practically significant) higher commitment than providing a convincing rationale for an assigned goal. In addition, self-set goals can be highly effective in gaining commitment, although they may not always be set as high as another person would assign (Locke 1996). Indeed, improvement goals can also be set from the outside, for instance based on benchmarking (Kelly 2016), by top down target setting from upper management through the translation of the (operations) strategy, but it can also be set up internally by means of so-called board sessions and daily stand-up meetings (Kilduff, Funk, and Mehra 1997). By having employees brainstorm themselves what could be better, what the improvement potential is, there is more commitment and involvement of employees to realise these goals.

5.2. Managerial implications

This study shows that training for continuous improvement should not only be given about the common improvement method, but especially broad in the field of continuous improvement. If training is given in the general improvement process, in the tactical practices to be used and in the mandatory operational tools and practical techniques (e.g. 5-times-why, value stream mapping, pareto analysis) then the relationships between the tools ('this is a kanban mechanism') and the practices ('which we use in a pull system to limit work in progress') must be explained. Rarely are the theoretical foundations underlying the tools and practices, such as the factory physics laws of operations management ('because according to Little's law, the lead time will remain relatively short') discussed in those training sessions, let alone that a clear link has been made with the operations strategy of the organisation ('because that is important in view of our strategic focus on shortening lead times') what may be desired or even necessary in different environments (e.g. high-tech production or professional services). Hence, training for continuous improvement must be done in a broad sense, with the common improvement method being embedded in theoretical and practical components of continuous improvement, taking into account the individual and strategic significance of continuous improvement for the organisation. Indeed, this study shows that it is advisable to coordinate any training on continuous improvement and the common improvement method with the needs of both the organisation and those individuals involved and to conduct it just-in-time.

5.3. Limitations and future research

This study is subject to several limitations, of which we will discuss the main ones. First the cross-sectional research design limits the extent to which cause-effect relationships can be inferred. This limitation can be addressed in future research through the collection of longitudinal data. Second, since perceptual data is used to measure the (performance) constructs of this study, the use of multiple informants to verify perceptions would be a logical extension, especially since employee involvement was proposed as a moderating variable using participants' perception of the level of employee involvement in continuous improvement in their organisations. In addition, since respondents were participants of a part-time executive master's course, one could argue that respondents have a positive attitude towards the research issues. Despite the absence of overly skewed variables in our sample, we must be cautious to generalise the findings of this study.

Third, in this study, participative goal setting for CI was measured based on items from the participative decision-making scale of the empowering leadership questionnaire of Arnold et al. (2000) where we reworded the items to fit the context of continuous improvement. Though this scale has a value of Cronbach's alpha of .79, it would be good to validate this scale in more detail on other samples and to assess the extent to which it acts as a moderator for other variables in relation to continuous improvement. This is also the case for the newly developed scale for common improvement method that was based on the work of Zu, Fredendall, and Douglas (2008) . Fourth, it is interesting to study the orientation and attribution of employees towards a common improvement method and other infrastructural variables in order to better understand the mechanisms by a continuous infrastructure affect continuous improvement. Future research designs should also include self-efficacy for continuous improvement as an important variable to understand the effect of infrastructural variables such as training on continuous improvement. Despite these limitations and ideas for further investigations, we believe that our study has extended current understanding about training and the use of a common improvement method as important infrastructural variables to facilitate continuous improvement.

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Source: https://www.tandfonline.com/doi/full/10.1080/09537287.2020.1716405

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